9.8k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- California Institute of TechnologyUS101 papers
- Massachusetts Institute of TechnologyUS100 papers
- Columbia UniversityUS97 papers
- Monash UniversityAU97 papers
- Stanford UniversityUS97 papers
- University of MichiganUS97 papers
- University of MinnesotaUS97 papers
- Australian National UniversityAU96 papers
- California State University, FullertonUS96 papers
- Cardiff UniversityGB96 papers
- Leibniz University HannoverDE96 papers
- LIGO Scientific CollaborationUS96 papers
11 papers · 1 filter
Cornserve: A Distributed Serving System for Any-to-Any Multimodal Models
Jae-Won Chung, Jeff J. Ma, Jisang Ahn +4
Any-to-Any models are an emerging class of multimodal models that accept combinations of multimodal data (e.g., text, image, video, audio) as input and generate them as output. Ser…
Parallel Complex Diffusion for Scalable Time Series Generation
Rongyao Cai, Yuxi Wan, Kexin Zhang +4
Diffusion models learn data distributions indirectly through denoising, making the difficulty of generative modeling closely tied to the dependency structure of data. For time seri…
Evaluation and Benchmarking of LLM Agents: A Survey
Mahmoud Mohammadi, Yipeng Li, Jane Lo +1
The rise of LLM-based agents has opened new frontiers in AI applications, yet evaluating these agents remains a complex and underdeveloped area. This survey provides an in-depth ov…
Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting
Yingtao Luo, Shikai Fang, Binqing Wu +2
Weather forecasting is essential but remains computationally intensive and physically incomplete in traditional numerical weather prediction (NWP) methods. Deep learning (DL) model…
Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment Labels
Yaxuan Wang, Hao Cheng, Jing Xiong +6
Detecting anomalies in temporal data has gained significant attention across various real-world applications, aiming to identify unusual events and mitigate potential hazards. In p…
A Systematic Review of Machine Learning Approaches for Detecting Deceptive Activities on Social Media: Methods, Challenges, and Biases
Yunchong Liu, Xiaorui Shen, Yeyubei Zhang +4
Social media platforms like Twitter, Facebook, and Instagram have facilitated the spread of misinformation, necessitating automated detection systems. This systematic review evalua…
Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting
Tianxiang Zhan, Yuanpeng He, Yong Deng +3
In practical scenarios, time series forecasting necessitates not only accuracy but also efficiency. Consequently, the exploration of model architectures remains a perennially trend…
DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series
Zahra Zamanzadeh Darban, Yiyuan Yang, Geoffrey I. Webb +4
In time series anomaly detection (TSAD), the scarcity of labeled data poses a challenge to the development of accurate models. Unsupervised domain adaptation (UDA) offers a solutio…
Interpretable Automated Machine Learning in Maana(TM) Knowledge Platform
Alexander Elkholy, Fangkai Yang, Steven Gustafson
Machine learning is becoming an essential part of developing solutions for many industrial applications, but the lack of interpretability hinders wide industry adoption to rapidly…
PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making
Fangkai Yang, Daoming Lyu, Bo Liu +1
Reinforcement learning and symbolic planning have both been used to build intelligent autonomous agents. Reinforcement learning relies on learning from interactions with real world…
SoftTarget Regularization: An Effective Technique to Reduce Over-Fitting in Neural Networks
Armen Aghajanyan
Deep neural networks are learning models with a very high capacity and therefore prone to over-fitting. Many regularization techniques such as Dropout, DropConnect, and weight deca…